vrm_system = VRMSimulationModel(assembly_type, assembly_kccs, assembly_kpis, part_name, part_type, voxel_dim, voxel_channels, point_dim, aritifical_noise) deploy_model = BayesDeployModel() #Generate Paths train_path = '../trained_models/' + part_type model_path = train_path + '/model' + '/Bayes_trained_model_0' logs_path = train_path + '/logs' deploy_path = train_path + '/deploy/' plots_path = train_path + '/plots/' #Voxel Mapping File get_data = GetTrainData() print('Importing and Preprocessing Cloud-of-Point Data') dataset = [] dataset.append(get_data.data_import(file_names_x, data_folder)) dataset.append(get_data.data_import(file_names_y, data_folder)) dataset.append(get_data.data_import(file_names_z, data_folder)) point_index = get_data.load_mapping_index(mapping_index) #Make an Object of the Measurement System Class measurement_system = HexagonWlsScanner(data_type, application, system_noise, part_type, data_format) #Make an Object of the Assembly System Class assembly_system = PartType(assembly_type, assembly_kccs, assembly_kpis, part_name, part_type, voxel_dim, voxel_channels,
logs_path = train_path + '/logs' pathlib.Path(logs_path).mkdir(parents=True, exist_ok=True) plots_path = train_path + '/plots' pathlib.Path(plots_path).mkdir(parents=True, exist_ok=True) # In[7]: #Objects of Measurement System, Assembly System, Get Inference Data print('Initializing the Assembly System and Measurement System....') measurement_system = HexagonWlsScanner(data_type, application, system_noise, part_type, data_format) vrm_system = VRMSimulationModel(assembly_type, assembly_kccs, assembly_kpis, part_name, part_type, voxel_dim, voxel_channels, point_dim, aritifical_noise) get_data = GetTrainData() kcc_sublist = cftrain.encode_decode_params['kcc_sublist'] output_heads = cftrain.encode_decode_params['output_heads'] encode_decode_multi_output_construct = config.encode_decode_multi_output_construct if (output_heads == len(encode_decode_multi_output_construct)): print("Valid Output Stages and heads") else: print("Inconsistent model setting") print("KCC sub-listing: ", kcc_sublist) #Check for KCC sub-listing if (kcc_sublist != 0): output_dimension = len(kcc_sublist)
pathlib.Path(plots_path).mkdir(parents=True, exist_ok=True) deployment_path = train_path + '/deploy' pathlib.Path(deployment_path).mkdir(parents=True, exist_ok=True) #Objects of Measurement System, Assembly System, Get Inference Data print('Initializing the Assembly System and Measurement System....') measurement_system = HexagonWlsScanner(data_type, application, system_noise, part_type, data_format) vrm_system = VRMSimulationModel(assembly_type, assembly_kccs, assembly_kpis, part_name, part_type, voxel_dim, voxel_channels, point_dim, aritifical_noise) get_data = GetTrainData() #print(input_conv_data.shape,kcc_subset_dump.shape) print('Building Unet Model') kcc_sublist = cftrain.encode_decode_params['kcc_sublist'] print("KCC sub-listing: ", kcc_sublist) #Check for KCC sub-listing if (kcc_sublist != 0): output_dimension = len(kcc_sublist) else: output_dimension = assembly_kccs print("Process Parameter Dimension: ", output_dimension)
pathlib.Path(plots_path).mkdir(parents=True, exist_ok=True) deployment_path = train_path + '/deploy' pathlib.Path(deployment_path).mkdir(parents=True, exist_ok=True) #Objects of Measurement System, Assembly System, Get Inference Data print('Initializing the Assembly System and Measurement System....') measurement_system = HexagonWlsScanner(data_type, application, system_noise, part_type, data_format) vrm_system = VRMSimulationModel(assembly_type, assembly_kccs, assembly_kpis, part_name, part_type, voxel_dim, voxel_channels, point_dim, aritifical_noise) get_data = GetTrainData() #print(input_conv_data.shape,kcc_subset_dump.shape) print('Building 3D CNN model') output_dimension = assembly_kccs dl_model = Multi_Head_DLModel(model_type, assembly_stages, output_dimension, categorical_kccs) model = dl_model.multi_head_standard_cnn_model_3d(voxel_dim, voxel_channels) print('Importing data') point_index = get_data.load_mapping_index(mapping_index) kcc_dataset = get_data.data_import(kcc_files, kcc_folder)
kmc_path = train_path + '/kmc' pathlib.Path(kmc_path).mkdir(parents=True, exist_ok=True) kmc_plot_path = kmc_path + '/plots' pathlib.Path(kmc_plot_path).mkdir(parents=True, exist_ok=True) print('Initializing the Assembly System and Measurement System....') measurement_system = HexagonWlsScanner(data_type, application, system_noise, part_type, data_format) vrm_system = VRMSimulationModel(assembly_type, assembly_kccs, assembly_kpis, part_name, part_type, voxel_dim, voxel_channels, point_dim, aritifical_noise) get_data = GetTrainData() print('Importing and preprocessing Cloud-of-Point Data') dataset = [] dataset.append((get_data.data_import(file_names_x, data_folder)).iloc[:, 0:point_dim]) dataset.append((get_data.data_import(file_names_y, data_folder)).iloc[:, 0:point_dim]) dataset.append((get_data.data_import(file_names_z, data_folder)).iloc[:, 0:point_dim]) kcc_dataset = get_data.data_import(kcc_files, kcc_folder) point_index = get_data.load_mapping_index(mapping_index) point_data = pd.concat([dataset[0], dataset[1], dataset[2]], axis=1,
system_noise = config.assembly_system['system_noise'] aritifical_noise = config.assembly_system['aritifical_noise'] data_folder = config.assembly_system['data_folder'] kcc_folder = config.assembly_system['kcc_folder'] kcc_files = config.assembly_system['test_kcc_files'] print('Initializing the Assembly System and Measurement System....') measurement_system = HexagonWlsScanner(data_type, application, system_noise, part_type, data_format) vrm_system = VRMSimulationModel(assembly_type, assembly_kccs, assembly_kpis, part_name, part_type, voxel_dim, voxel_channels, point_dim, aritifical_noise) deploy_model = DeployModel() get_data = GetTrainData() #Generate Paths train_path = '../trained_models/' + part_type model_path = train_path + '/model' + '/trained_model_0.h5' logs_path = train_path + '/logs' deploy_path = train_path + '/deploy/' #Import all static resources #import Model inference_model = deploy_model.get_model(model_path) point_index = get_data.load_mapping_index(mapping_index) cop_file_name = vc.voxel_parameters['nominal_cop_filename'] file_path = '../resources/nominal_cop_files/' + cop_file_name #Read cop from csv file nominal_cop = vrm_system.get_nominal_cop(file_path)
pathlib.Path(logs_path).mkdir(parents=True, exist_ok=True) plots_path=train_path+'/plots' pathlib.Path(plots_path).mkdir(parents=True, exist_ok=True) deployment_path=train_path+'/deploy' pathlib.Path(deployment_path).mkdir(parents=True, exist_ok=True) print('Initializing....') measurement_system=HexagonWlsScanner(data_type,application,system_noise,part_type,data_format) print('Measurement system initialized') vrm_system=VRMSimulationModel(assembly_type,assembly_kccs,assembly_kpis,part_name,part_type,voxel_dim,voxel_channels,point_dim,aritifical_noise) print('Assembly and simulation system initialized') get_data=GetTrainData(); metrics_eval=MetricsEval(); point_index=get_data.load_mapping_index(mapping_index) print('Support systems initialized') kcc_struct=kcc_config.kcc_struct sampling_config=sampling_config.sampling_config adaptive_sampling=AdaptiveSampling(sampling_config['sample_dim'],sampling_config['sample_type'],sampling_config['adaptive_sample_dim'],sampling_config['adaptive_runs']) output_dimension=assembly_kccs eval_metrics_type= ["Mean Absolute Error","Mean Squared Error","Root Mean Squared Error","R Squared"]
deployment_path = train_path + '/deploy' pathlib.Path(deployment_path).mkdir(parents=True, exist_ok=True) print('Initializing....') measurement_system = HexagonWlsScanner(data_type, application, system_noise, part_type, data_format) print('Measurement system initialized') vrm_system = VRMSimulationModel(assembly_type, assembly_kccs, assembly_kpis, part_name, part_type, voxel_dim, voxel_channels, point_dim, aritifical_noise) print('Assembly and simulation system initialized') get_data = GetTrainData() metrics_eval = MetricsEval() point_index = get_data.load_mapping_index(mapping_index) print('Support systems initialized') kcc_struct = kcc_config.kcc_struct sampling_config = sampling_config.sampling_config adaptive_sampling = AdaptiveSampling( sampling_config['sample_dim'], sampling_config['sample_type'], sampling_config['adaptive_sample_dim'], sampling_config['adaptive_runs']) output_dimension = assembly_kccs